IJSTR

International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us
CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT
QR CODE
IJSTR-QR Code

IJSTR >> Volume 4 - Issue 12, December 2015 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

[Full Text]

 

AUTHOR(S)

Md. Abdullah-al-mamun, Mustak Ahmed

 

KEYWORDS

Index Terms: Pattern Recognition, Multi-Layer Perceptron, MLP, Artificial Neural Network, ANN, Backpropagation, Supervised learning

 

ABSTRACT

Abstract: Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain (called, Artificial Neural Network) that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because, the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research, now a day’s pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural network(in the algorithm of artificial Intelligence) as the best possible way of utilizing available resources to make a decision that can be a human like performance.

 

REFERENCES

[1] E. Backer, “Computer-Assisted Reasoning in Cluster Analysis” Prentice Hall, 1995.

[2] B. Ripley, "Statistical Aspects of Neural Networks", Networks on Chaos: Statistical and Probabilistic Aspects. U. Bornndorff-Nielsen, J. Jensen, and W. Kendal, eds., Chapman and Hall, 1993.

[3] Violeta sandu, Florin Leon, "RECOGNITION OF HANDWRITTEN DIGITS USING MULTILAYER PERCEPTRONS", Universitatea Tehnică „Gheorghe Asachi” din Iaşi Tomul LV (LIX), Fasc. 4, 2009.

[4] Anil K. Jain, Fellow, IEEE, Robert P.W. Duin, and Jianchang Mao, Senior Member, IEEE, “Statistical Pattern Recognition: A Review” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, january 2000, pp. 4-37.

[5] S. Watanabe, “Pattern Recognition: Human and Mechanical” New York: Wiley, 1985.

[6] Bishop, Christopher M. (2006), "Pattern Recognition and Machine Learning" Springer. p. vii.

[7] http://aitopics.org/topic/pattern-recognition, - Pattern Recognition Laboratory at Delft University of Technology

[8] R. Picard, Affective Computing. MIT Press, 1997.

[9] En Wikipedia, “Pattern Recognition” June 17, 2015.

[10] En Wikipedia, “Multilayer Perceptron”, June 22, 2015.

[11] En Wikipedia, “Backpropagation”, June 22, 2015.

[12] Jayanta Kumar Basu, Debnath Bhattacharyya, Tai-hoon Kim, "Use of Artificial Neural Network in Pattern Recognition" , International Journal of Software Engineering and Its Applications, Vol. 4, No. 2, April 2010.

[13] Tin Kam Ho, Mitra Basu and Martin Hiu Chung Law , "Data Complexity in Pattern Recognition", ISBN 978-1-84628-172-3 , 2006

[14] Daniel Admassu, "Unicode Optical Character Recognition", Codeproject.com in 23 Aug 2006.

[15] Andrew R. Webb, "Statistical Pattern Recognition", ISBNs: 0-470-84513-9 (HB); QinetiQ Ltd., Malvern, UK.

[16] R Beale and T jackson, “Neural Computing: An introduction”, Adam Hilger, Bristol, Philadelphia and New York.

[17] Md. Rabiul Islam and Kaushik Roy, “An Approach to Implement the real time eye recognition system using artificial neural network”, Proceeding of the ICEECE, December 22-24, Dhaka, Bangladesh.

[18] Tin Kam Ho, Mitra Basu and Martin Hiu Chung Law, "Data Complexity in Pattern Recognition", ISBN 978-1-84628-172-3, 2006.

[19] Christopher M. Bishop, "Neural Networks for Pattern Recognition", Clarendon Press-OXFORD, 1995.

[20] S. Watanabe, ed., “Frontiers of Pattern Recognition” New York: Academic Press, 1972.

[21] "View-invariant action recognition based on Artificial Neural Networks", IEEE 2012 Transactions on Neural Networks and Learning Systems, Volume: 23 , Issue: 3.